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Self-generation ART Neural Network for Character Recognition

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

In this paper, we present a novel self-generation, supervised character recognition algorithm based on adaptive resonance theory (ART) artificial neural network (ANN) and delta-bar-delta method. By combining two methods, the proposed algorithm can reduce noise problem in the ART ANN and the local minima problem in the delta-bar-delta method. The proposed method can extend itself based on new information contained in input patterns that require nodes of hidden layers in neural networks and effectively find characters. We experiment with various real-world documents such as a student ID and an identifier on a container. The experimental results show that the proposed self-generation. ART algorithm reduces the possibility of local minima and accelerates learning speed compared with existing.

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Author information

Authors and Affiliations

  1. Image Processing and Intelligent Systems Laboratory, Department of Image Engineering, Graduate School of Advanced Imaging Science, Multimedia, and Film, Chung-Ang University, Seoul, Korea

    Taekyung Kim & Joonki Paik

  2. Department of Computer Engineering, College of Electronics and Information, Kwangwoon University, Seoul, Korea

    Seongwon Lee

Authors
  1. Taekyung Kim
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  2. Seongwon Lee
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  3. Joonki Paik
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Kim, T., Lee, S., Paik, J. (2006). Self-generation ART Neural Network for Character Recognition. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_41

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  • DOI: https://doi.org/10.1007/11760023_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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